The invention described herein relates generally to surface inspection and testing. In particular, the invention relates to methods for identification in surfaces and substrates used in semiconductor fabrication and processing.
For many years, various brightfield, darkfield, and e-beam scanning methodologies have been used to inspect surfaces. These scanning technologies make use of light scattered and/or reflected by a surface to characterize and examine features of the surface. The details of these and other related scanning and inspection technologies are well known to those having ordinary skill in the art.
In many of these type devices, an inspection surface is secured in an inspection device and then a light beam is projected on the inspection surface. The light beam is then scanned across the portions of the surface that are to be inspected. Appropriately placed detectors detect light from the inspection surface. The detectors generate signals corresponding to the detected light. These signals are then processed using a variety of different methodologies to determine various surface characteristics. Of particular interest are surface features that are referred to as defects. The detection and quantification of defects is important in many areas. In particular, defect detection and analysis are important in semiconductor processing. Defects include, but are not limited to, particles, pits, bumps, scratches, and a number of other features that mar the inspection surface.
Although existing machines and processes accomplish their designed purposes exceptionally well, they have some limitations. Existing machines and processes can detect defects in highly polished regular surfaces very well, but they can have difficulty detecting defects in certain non-uniform surfaces. In one example, currently used detection techniques have difficulties detecting the presence of defects in patterned surfaces. Conventional techniques have difficulties discerning between changes in a surface pattern and the presence of a defect. Such patterned surfaces include, but are not limited to, patterned semiconductor wafer surfaces and patterns formed on masks. Conventional processes are also known to have some difficulties detecting defects in surfaces that have other types of non-uniform surface characteristics. Surfaces having areas of differing surface properties can make defect detection a difficult prospect. For example, an inspection surface having relatively polished regions and also having regions of significantly greater surface roughness can present inspection difficulties. Using conventional inspection processes on such surfaces can result in failures to detect small defects and also the detection of xe2x80x9cfalse positivesxe2x80x9d. False positives are instrument readings that indicate the presence of a defect where no defect actually exists. These false positives are a serious problem for reasons that are discussed in greater detail hereinbelow.
For these and other reasons, improved surface inspection methodologies are needed.
In accordance with the principles of the present invention, a method of surface inspection is disclosed. Generally, the method scans the inspection surface to obtain surface measurements. Determinations of various noise levels in the surface are made based on variations in the surface measurements. A dynamic threshold is then determined based on the varying noise levels in the surface. The dynamic threshold adapts to the noise levels in the inspection surface to provide a varying threshold that adjusts to areas of high and low surface noise in the same inspection surface. In some embodiments, such a varying threshold involves adjusting the sensitivity of the threshold based on the surface noise levels. Defects are then identified by comparing surface measurements with the dynamic threshold.
In one method embodiment, the surface is scanned to obtain surface measurements. The surface measurements are used to generate a baseline. A dynamic threshold associated with the surface measurements and the baseline is generated. Defects are identified using comparisons of surface measurements with at least one of the baseline and the dynamic threshold.
The embodiments of the invention also include a surface inspection method that uses signal-to-noise ratios to identify defects. Such an embodiment scans an inspection surface to obtain surface measurements. Noise levels associated with the inspection surface are then determined. Signal-to-noise ratios are determined for the surface measurements. The signal-to-noise ratios are compared with a signal-to-noise ratio threshold value. Defects are identified based on the comparisons of the signal-to-noise ratio of the surface measurements with the signal-to-noise ratio threshold value.
These and other aspects of the present invention are described in greater detail in the detailed description of the drawings set forth hereinbelow.